{"title":"Workflow Similarity Measure for Process Clustering in Grid","authors":"Yi Wang, Minglu Li, Jian Cao, Xinhua Lin, F. Tang","doi":"10.1109/FSKD.2007.618","DOIUrl":null,"url":null,"abstract":"In grid environment, workflow process can be seen as not only cooperative approach of grid services and resources, but also reusable and sharable knowledge to settle specific problem. The research of grid workflow process clustering can promote knowledge discovery and reuse in grid. In this paper, we put forward a grid workflow process design method using event-condition-action (ECA) rule, and propose a new process similarity measure approach. Then, we use a case to prove the feasibility of the approach and show how to revise present clustering algorithm with the similarity measure approach briefly.","PeriodicalId":201883,"journal":{"name":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FSKD.2007.618","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In grid environment, workflow process can be seen as not only cooperative approach of grid services and resources, but also reusable and sharable knowledge to settle specific problem. The research of grid workflow process clustering can promote knowledge discovery and reuse in grid. In this paper, we put forward a grid workflow process design method using event-condition-action (ECA) rule, and propose a new process similarity measure approach. Then, we use a case to prove the feasibility of the approach and show how to revise present clustering algorithm with the similarity measure approach briefly.